Andrew S. Manikas

The International Journal of Production Research at 55: a content-driven review and analysis

The articles published in the International Journal of Production Research (IJPR) since inception have made a significant contribution to operations management (OM) research, firmly establishing IJPR as one of the most important outlets for OM research. This paper uses a text mining technique called Latent Semantic Analysis to identify the core areas of research published in IJPR since inception, and reveals how the focus on topics has evolved over time. The data consist of the abstracts of all articles published in IJPR from the inception of the journal through December 2015. The study identifies 16 core areas of research and provides a detailed analysis of how these core areas have evolved over time. The results from this data-driven analysis of 55 years of research in IJPR not only provide a comprehensive examination of past research in the journal but also important insights into the evolution of key areas of research in operations management.

An analysis of research methods in IJPR since inception

Production research as an academic field has experienced tremendous growth in the last few decades. The progress in production research and operations management (OM) research is due in no small part to the increasing sophistication and availability of research methods in this field. This paper explores the role of research methods in OM publications through an analysis of the entire corpus of research as represented in a leading OM journal, the International Journal of Production Research (IJPR). This paper reports on a study of all 8653 academic article abstracts published in IJPR since inception to identify the research methods used to both generate and analyse data over the 55 years from the journal’s inception in 1961 through 2015. The study classifies articles using a 6 × 6 typology on the dimensions of data generation and data analysis and provides a summary of the use of research methods and the evolution of their use over time. For example, mathematical modelling has become the dominant method for data generation while experiments have become less popular. Though meta-heuristics and optimisation remain the most popular methods for data analysis, data mining methods have gained pained popularity, comparable to statistical methods.

An exploration of ‘sticky’ inventory management in the manufacturing industry

Abstract Traditional models examining relationships between firm resources and revenues assume that the many expenses and asset holdings change in proportion to changes in demand. However, research has found that for many costs and assets assumed to be variable, the magnitude of a change in a cost or asset in proportion to a change in revenue is smaller during periods when revenue decreases compared to the change in the cost or asset when revenue increases. Costs and assets which behave in this manner have been denoted as ‘sticky’ costs or assets. This study examines if inventory in the manufacturing industry is managed in a ‘sticky’ manner and what implications inventory stickiness has on firm performance. Utilising firm panel data over a 25-year time window we find that inventory stickiness does exist amongst manufacturers and that it has negative implications for firm performance.

Leveraging Academic Partnerships to Improve Logistics at Nonprofit Organizations

This article presents the results of a partnership between a nonprofit organization and a team of academic researchers that developed a low-cost spreadsheet-based tool that allows organizations to effectively schedule vehicle operations. Specifically, the tool (1) handles the real-world constraints present in moderately complex logistics environments; and (2) uses general computing hardware and software that is already deployed in most organizations, thereby rendering the solution radically low cost (effectively free). We deployed this tool to a humanitarian organization, the Idaho Foodbank, which realized a substantial improvement in its fleet efficiency and a corresponding reduction in route-planning time. The methodology used to manage this collaboration with academia can be leveraged by other nonprofit organizations attempting to overcome the financial barriers that commonly prevent budget-constrained organizations from accessing advanced technologies.

Metro Meals on Wheels Treasure Valley Employs a Low-Cost Routing Tool to Improve Deliveries

In this paper, we discuss a project in which we develop a spreadsheet-based system that interfaces with a no-fee driving-directions application programming interface to quickly and accurately build a travel-time and distance matrix, and then rapidly determine near-optimal delivery-route schedules using a modified genetic algorithm. To the best of our knowledge, the method we used to create the travel matrix had not been studied previously. The tool was tested and refined in a humanitarian setting—a local branch of the Meals on Wheels Association of America (now Meals on Wheels America), an organization that combats hunger and poverty by providing food to individuals who are in need. The tool, which is currently being utilized by Metro Meals on Wheels Treasure Valley, has substantially reduced the time required to plan deliveries and has also reduced the delivery driving times by approximately 15 percent.